A comprehensive real-time embedded and IoT-based system designed to monitor vehicle health parameters and driver safety conditions using an automotive-grade CAN communication network and cloud-based alerting. The system enables real-time monitoring, fault detection, and proactive alerts for improved safety and reliability.
This project presents a real-time Vehicle Health Monitoring and Driver Alert System designed to enhance vehicle safety and reliability. The system continuously monitors engine operating conditions and driver hand presence on the steering wheel, processes the data locally, and communicates it using an automotive-grade CAN protocol.
Engine-related parameters are analyzed in real time to detect abnormal conditions, while the driver alert mechanism identifies unsafe driving behavior such as removing hands from the steering wheel. The processed information is displayed locally on a TFT display and simultaneously transmitted to the cloud for remote monitoring.
An event-driven alert mechanism generates email notifications whenever predefined safety thresholds are exceeded, enabling early fault detection and proactive response. The overall system follows a scalable, reliable, and automotive-style architecture, making it suitable for real-world vehicle monitoring and driver safety applications.
This block diagram shows the transmitter–receiver architecture of the system, where sensor data is processed by STM32, transmitted over CAN, and sent to the cloud via ESP32.
Continuous monitoring of critical engine parameters:
- Engine temperature
- Engine oil level
- Engine vibration
The collected data is analyzed to evaluate engine health and detect abnormal operating conditions.
- Monitoring of driver hand presence on the steering wheel
- Dual touch-sensor logic to detect unsafe hand removal
- Alerts generated when unsafe driving behavior is detected
- Reliable and real-time data transfer using CAN protocol
- Sensor data transmitted between ECUs with error detection
- Automotive-grade communication ensures robustness and noise immunity
- Real-time system status and sensor values displayed on a TFT display connected to ESP32
- Ensures local monitoring even without cloud connectivity
- Sensor data published to AWS IoT using MQTT
- Enables remote monitoring and system analysis
- Supports scalability for fleet or multi-vehicle applications
- Predefined threshold-based alert mechanism
- AWS SNS used to generate real-time email alerts
- Alerts triggered during abnormal engine conditions or unsafe driving behavior
- Embedded C for STM32 firmware development
- Arduino / ESP-IDF for ESP32 programming
- CAN protocol using MCP2551 CAN controller
- FreeRTOS for real-time task management
- AWS IoT Core (MQTT) for cloud communication
- AWS SNS for email alert notifications
- Sensor interfacing and ECU integration
- CAN bus configuration between nodes
- ESP32 gateway setup for display and IoT
- Sensor data acquisition and processing
- CAN message framing and transmission
- ESP32 data reception and TFT display update
- MQTT data publishing to AWS IoT
- AWS IoT device and policy configuration
- MQTT topic creation
- AWS IoT rules for threshold detection
- SNS topic and email subscription setup
- Sensor calibration and validation
- CAN communication reliability testing
- Threshold-based alert testing
- End-to-end data flow verification
The above image shows the complete hardware implementation of the system, including the STM32 controller, ESP32 gateway, sensors, CAN interface, and display modules mounted on a prototype board.
- Real-time vehicle health monitoring
- Improved driver safety through alerts
- Reliable CAN-based communication
- Cloud-based remote monitoring
- Reduced maintenance cost through early fault detection
- Scalable architecture for real-world deployment
📌 Refer to the OUTPUT_IMAGES folder for real-time working photos, debugging screenshots, and cloud alert demonstrations.
The proposed system successfully demonstrates a real-time, CAN-based vehicle health monitoring and driver alert solution with IoT cloud integration. Its scalable and reliable architecture makes it suitable for modern automotive and fleet monitoring applications.
- Integration of additional vehicle sensors (RPM, TPMS, battery health)
- Predictive maintenance using data analytics
- Mobile or web dashboard for monitoring
- Enhanced security for CAN and IoT communication